RECURSOS PARA LA EDUCACIÓN

Participants

We recruited 38 Division I college football players from the University of North Carolina at Chapel Hill Fall 2012 football team (age = 20.4±1.4 years; height = 190.2±6.7 cm; mass = 109.3±17.8 kg). Participants were selected based on input from the coaching and sports medicine staff to include a variety of player positions including 2

quarterbacks, 3 wide receivers, 3 offensive backs, 12 offensive linemen (including tight ends), 12 defensive backs (including linebackers), and 6 defensive linemen. All

participants signed an informed consent approved by the University of North Carolina’s Institutional Review Board prior to participation in study. Inclusion criteria required that participants must be a University of North Carolina at Chapel Hill Division I collegiate football player during the Fall 2012 season, who wore a helmet equipped with the Head Impact Telemetry System, and consented to the study. Exclusion criteria included anyone who has a history of permanent vision loss or is currently symptomatic from a head, neck, or eye injury that would negatively affect scores on visual and sensory performance tasks.

29 Instrumentation

Head Impact Telemetry System

The Head Impact Telemetry System (Simbex, Lebanon, NH) was used to collect data on linear acceleration, rotational acceleration, and Head Impact Technology severity profile (HITsp). The HIT System is comprised of six spring-loaded single-axis

accelerometers inserted into Riddell VSR4 (sizes: L or XL), Revolution (sizes: M, L, or XL), or Revolution Speed (sizes: M, L, or XL) football helmets (Riddell Corporation) and the Sideline Response System. The in-helmet accelerometers are strategically placed to allow for measurement of linear and rotational acceleration and impact location. Up to 100 separate head impacts can be stored in the memory built into the accelerometer. The accelerometers collect data at 1 kHz for a period of forty milliseconds; eight milliseconds are recorded before the data collection trigger and thirty-two milliseconds of data are collected after the trigger. The HIT System can collect data from up to 64 players over a distance greater than the length of a football field.

The Sideline Response System was located on the sideline during games and practices. This unit receives time-stamped, encoded data from the in-helmet

accelerometers through a radiofrequency telemetry link. The data are processed through a novel algorithm to determine location and magnitude of impacts (Crisco, Chu et al. 2004). The user can access these data through the Head Impact Telemetry Impact Analyzer software on laptop in the Sideline Response System unit. The HIT System measures linear acceleration (measured in terms of gravitational acceleration, g),

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(HITsp). The HITsp is a weighted composite score encompassing linear and rotational accelerations, Gadd Severity Index, Head Injury Criterion, and impact location. The HIT System is a valid measure of head impact biomechanics (Duma, Manoogian et al. 2005).

Visual and Sensory Performance Assessment

The Nike SPARQ Sensory Station is an evaluation and training tool of visual and sensory performance designed for athletes. The Nike SPARQ Sensory Station is an interactive touch screen device consists of a single computer that controls two high- resolution LCD monitors (one twenty-two inch and one forty-two inch monitor). An Apple iPod touch is also used for some of the assessments (Erickson, Citek et al. 2011). See Table 2.1 for description and testing procedures for each evaluation component.

The Nike SPARQ Sensory Station has been found to be a reliable measure of visual and sensory performance with no significant changes in performance between multiple sessions on visual clarity, contrast sensitivity, depth perception, target capture, perception span, and reaction time. However, an expected learning effect was found for performance on Near-Far Quickness, Eye-Hand Coordination and Go/No Go across two testing sessions separated by a period of about one week (Erickson, Citek et al. 2011).

Reaction Time Assessments

The subjects underwent a series of reaction time assessments including the computerized tests CNS Vital Signs and Automated Neuropsychological Assessment Metrics (ANAM), and the Clinical Reaction Time Apparatus. The Nike SPARQ Sensory Station also includes a test of reaction time. Subjects completed the entire test on the Nike SPARQ Sensory Station, but reaction time scores were used in the comparison to the previously mentioned assessments.

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CNS Vital Signs (CNS Vital Signs, LLC, Chapel Hill, NC) is a series computerized neurocognitive test that was can detect changes in neurocognitive

performance over time. Participants only completed the Stroop test, which measures the ability to react to a simple, but increasingly difficult set of directions. See Table 3.1 for a complete description of the procedures for this test. The reaction time domain score is calculated using the following equation: [Stroop Test (ST) Complex Reaction Time Correct + Stroop Reaction Time Correct] /2. CNS Vital Signs has been found to be valid and reliable (Gualtieri and Johnson 2006).

Automated Neuropsychological Assessment Metrics (Vista LifeSciences,

Washington D.C.) is a series of computerized neurocognitive tests that was developed by the United States Military’s Office of Military Performance Assessment Technology to detect changes in neurocognitive performance overtime. (Kabat, Kane et al. 2001). Our study used the simple reaction time test, in which the individual is instructed to press the mouse key upon the presentation of a simple stimulus of an asterisk on the screen. Our study also used the procedural reaction time test, in which the individual is tested on both reaction time and processing speed. The individual is presented with one of the numerals 2, 3, 4, and 5 and respond by clicking the left mouse button if the stimulus is a 2 or 3 and clicking the right mouse button if the stimulus is a 4 or 5. ANAM has been found to be valid and reliable (Kabat, Kane et al. 2001; Segalowitz, Mahaney et al. 2007).

The Clinical Reaction Time Apparatus was developed to give clinicians a simple and inexpensive measure of reaction time that could be used on the sideline or in an athletic training room. This device is a thin, rigid cylinder with a weighted disk attached to the bottom. The examiner holds and releases the apparatus while the individual reacts

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and catches it as quickly as possible using a pinch grip. Subjects completed two practice trials followed by eight trials in which the examiner released the apparatus at pre-

determined randomized time intervals ranging from two to five seconds. The examiner noted the measured distance at which the most superior portion of the subject’s pinch grip makes contact with the apparatus. A trial in which the subjects dropped the apparatus was noted as a “drop” and was not included as part of the calculation of clinical reaction time. The Clinical Reaction Time Apparatus has been found to be a valid and reliable measure of reaction time (Eckner, Whitacre et al. 2009).

Video Evaluation

The retrospective analysis of collision anticipation used previously analyzed video footage and head impact biomechanical data from the Fall 2010 season. Impacts were evaluated using the Player-to-Player Collision Type Evaluation Form that we developed for our previous research in this area. Intrarater reliability was tested by selecting and evaluating a subset of cases using the form, and then re-evaluating them thirty days after initial evaluation (k=.88) (Ocwieja, Mihalik et al. 2012). The Player-to- Player Collision Type Evaluation Form evaluates the following components: play type, closing distance, starting stance of player and opponent, whether the player was striking or being struck, whether the player was looking ahead or in the direction of the collision, ball possession, infraction type, movement of player and opponent, and overall

impression of the level of anticipation based on these factors. (See Appendix A: The Player-to-Player Collision Type Evaluation Form).

33 Procedures

Subjects underwent a single testing at the beginning of the Fall 2012 season. A trained clinician administered the testing session in a quiet controlled environment at the Matthew Gfeller Sport-Related Traumatic Brain Injury Research Center (Chapel Hill, NC). All subjects completed the tests in a counterbalanced order and received

standardized directions given by the administering clinician. The testing session took approximately 30-45 minutes. Subjects were not given any feedback regarding performance during the testing session. The testing session included the following assessments: Nike SPARQ Sensory Station, and reaction time tests on CNS Vital Signs, ANAM, and the Clinical Reaction Time Apparatus.

The team’s professional equipment manager fit subjects with an MxEncoder- equipped Riddell helmet at the beginning of the Fall 2012 season. Head impact data were collected during practices and games throughout the course of the season. The HIT System and Sideline Response System were checked on a weekly basis and prior to all games and practices, to ensure proper functioning.

The retrospective analysis of collision anticipation used previously analyzed video footage and head impact biomechanical data from the Fall 2010 season. Video footage was collected during all games and was filmed from two positions on the field: sideline and end zone. During the Fall 2010 season, a research assistant was responsible for setting up a video camera to record the game clock during competition and for synchronizing the time to ensure that the video footage could be linked to the head impact biomechanical data. Video footage was analyzed using the Player-to-Player

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Collision Type Evaluation Form. The principal investigator was blinded to the

biomechanical data during impact video analysis to allow for an unbiased analysis. Each impact was categorized as anticipated or unanticipated and as mild, moderate or severe. Data Reduction

For our first research question, we used data from the scores on traditional

reaction time tests (CNS Vital Signs, ANAM, and Clinical Reaction Time Apparatus) and the reaction time component of the Nike SPARQ Sensory Station evaluation. These scores were analyzed using Pearson correlations to determine the relationship between traditional measures of reaction time and reaction time as measured by the Nike SPARQ Sensory Station. One participant sustained a season-ending injury during the first week of practices, and another participant replaced his helmet with one incapable of supporting the HIT System technology. For these reasons, we did not have sufficient head impact biomechanical data and only used the scores from the initial testing session towards answering our first research question. This created a sample size of 38 participants for our first research question and 36 participants for our second research question.

For our second research question, we used raw data on visual and sensory performance that was exported from the Nike SPARQ Sensory Station. Scores for each individual test and the overall composite score were analyzed. We categorized subjects into two groups based on their performance on each assessment of the Nike SPARQ Sensory Station (High level of performance: ≥ 51st _{percentile; Low level of performance:}

≤ 49th percentile). These percentiles were based on our study’s sample. The following assessments had approximately equal number of subjects scoring in high and low

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performance groups, and thus were included in our analyses: Depth Perception, Near-Far Quickness, Target Capture, Perception Span, Eye Hand Coordination, Go/No Go, and Reaction Time. We also categorized subjects into high and low performance groups based on their performance on Visual Break and Reaction Time as measured by the Clinical Reaction Time Apparatus. Raw head impact data from the games and practices of the Fall 2012 season were exported from Sideline Response System using the Ridell Export Utility into Matlab 7 (The Mathworks, Inc., Natick, MA). Linear acceleration (g), rotational acceleration (rad/s2), and HITsp were the outcome measures of interest. All impacts under 10 g were removed because they are considered negligible with respect to head impact biomechanics and injury (Mihalik, Bell et al. 2007).

In order to allow for comparisons with previous research in this area, we categorized the head impact severity based on linear acceleration as mild (<66g), moderate (66-106g), or severe (>106g) and based on rotational acceleration as mild (<4600g), moderate (4600-7900g), or severe (>7900g) for our chi-square analyses (Zhang, Yang et al. 2004; Ocwieja, Mihalik et al. 2011). We used the two levels of visual and sensory performance (high and low) and three levels of impact severity (mild, moderate, severe) for our chi-square analyses to determine the association between level of visual and sensory performance and head impact severity. The two levels of visual and sensory performance (high and low) were also used in linear mixed model ANOVAs to determine differences in head impact biomechanics between groups. Our third

research question was retrospective. We used previously analyzed video footage from games played during the Fall 2010 season. The collisions were classified as

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form. Raw head impact data from the Fall 2010 season were exported from Sideline Response System using the Ridell Export Utility into Matlab 7 (The Mathworks, Inc., Natick, MA). Linear acceleration (g), rotational acceleration (rad/s2), and HITsp were the

outcome measures of interest. All impacts under 10 g were removed because they are

considered negligible with respect to head impact biomechanics and injury (Mihalik, Bell et al. 2007). In order to allow for comparisons with previous research in this area, we categorized the head impact severity based on linear acceleration as mild (<66g), moderate (66-106g) or severe (>106g) for our chi-square analyses (Zhang, Yang et al. 2004; Ocwieja, Mihalik et al. 2011). We used two levels of collision anticipation (anticipated, unanticipated) and three levels of head impact severity (mild, moderate, severe) in our chi-square analyses to determine the association between level of collision anticipation and head impact severity.

Data Analyses

All data were analyzed using SAS 9.3 statistical software with an a priori alpha level of 0.05. Pearson correlational analyses were used to assess the relationship between traditional measures of reaction time and reaction time as measured by the Nike SPARQ Sensory Station. Three separate random intercepts general linear mixed models were fit for linear acceleration, rotational acceleration, and HITsp. The large number of low magnitude head impacts skewed the distribution of head impacts; therefore, we used the natural logarithmic transformations for linear acceleration, rotational acceleration, and HITsp to create a normal distribution for statistical analyses.

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Prospective Chi-Square analyses were used to assess the association between level of visual and sensory performance (high and low) and an ordinal variable of impact severity (mild, moderate, severe) based on linear acceleration and rotational acceleration measures collected during head impacts that occurred during the Fall 2012 season. Linear mixed model ANOVAs were performed to analyze the differences in head impact biomechanics (linear acceleration, rotational acceleration, and HITsp) between high and low visual and sensory performers in each of the visual and sensory performance

assessments.

Retrospective Chi-Square analyses were performed to assess the association between level of anticipation (anticipated, unanticipated) and an ordinal variable of impact severity (mild, moderate, severe) based on linear and rotational acceleration measures that were collected during head impacts that occurred during the Fall 2010 season. Fisher’s Exact test was used in these Chi-Square analyses in order to account for the low number of unanticipated collisions.

38 Table 3.1. Data analysis plan

Question Description Variables of Interest Comparison Method

1 Prospective Is there a significant correlation between computerized and functional measures of reaction time and reaction time as measured by the Nike SPARQ Sensory Station? Traditional Measures • CNS Vital Signs Reaction Time Domain • ANAM Reaction Time • Clinical Reaction Time Apparatus Nike SPARQ Sensory Station • Reaction  Time   Test   Performance on traditional measures Performance on Nike SPARQ Sensory Station reaction time test Pearson Correlations 2 Prospective Is there a significant association between level of visual and sensory performance and head impact severity in college football players?

Nike SPARQ Sensory Station • Outcome measures (10) HIT System • Linear Acceleration • Rotational Acceleration • HITsp

Level of visual and sensory performance

• High  level  

• Low  level  

Head impact severity

• Mild   • Moderate   • Severe   Chi-Square Linear mixed model ANOVA 3 Retrospective Is there a significant association between collision anticipation and head impact severity in college football players? Collision Anticipation • Anticipated • Unanticipated HIT System • Linear Acceleration • Rotational Acceleration • HITsp Level of anticipation • Anticipated   • Unanticipated  

Head impact severity

• Mild  

• Moderate  

• Severe  

39 Table 3.2. Stroop Test

Test Portion Description

1 A color word will appear at the bottom of

the screen in black font. Press the space bar as soon as you see a word appear on the screen.

2 A color word will appear at the bottom of

the screen. Press the space bar as soon as you see the color of the word match what the word says

3 A color word will appear at the bottom of

the screen. Press the space bar as soon as you see the color word does not match what the word says

CHAPTER IV